The good news is that worldwide businesses are scaling up their digital and Artificial Intelligence (AI) efforts. Recent reports by Gartner, namely the Gartner CIO Agenda and Deloitte’s State of AI in Enterprise have shown that companies are stepping up their game to enter the digital era, with 33% of CIOs worldwide reporting they had evolved their digital endeavors to scale up from 17% the year before (Gartner, 2018), and 82% of AI adopters already reporting impressive ROIs (Deloitte, 2018)

Now the bad news. The reports also indicate 32% of businesses professionals have experienced an AI-related breach within the last two years. Fearing more cybersecurity breaches, 30% of respondents said they slowed initiatives (Deloitte, 2018). This coupled with the increased number of cyberattacks both in public and private enterprises has made cybersecurity a top concern for these early adopters of AI and Digital First approach.

Artificial Intelligence can be a double-edged sword. More powerful cyberattacks are expected as state-sponsored hackers and cyber-gangs deploy artificial intelligence, data science skills, algorithm-building skills or machine learning software to launch more sophisticated attacks. IBM’s 2018 study from the recent Black Hat cybersecurity conference indicates that hackers may use AI to develop new forms of malware.  IBM’s study says that AI malware is being designed in many ways to avoid detection by systems.

Cybersecurity, AI and Cloud Computing

As more large corporations begin to use cloud computing services, tech giants like Amazon, Alphabet and Microsoft are investing in AI startups to boost security. Alphabet launched its own cybersecurity business, Alphabet Chronicle, earlier this year.

Small businesses are equally at risk for a cybersecurity breach. In 2017, 61% small businesses were hit by cyberattacks, up from 55 percent the year before. The average cost of these attacks which typically exceed $1 million could easily drive small businesses to bankruptcy.

How AI and machine learning can help in cybersecurity

Enterprises find that scaling security with conventional systems is not enough to counter the new wave of cybercrime. Most conventional security systems are rules and signature-based which allows them to prepare for known attacks and known problems based on historical data. But cybercriminals are coming up with newer and more innovative ways to hack into systems, which presents a challenge for the security system. Additionally, the increased number of security alerts that the system triggers off usually overwhelms IT security teams.  This is where AI steps in.

AI and machine learning are increasingly being used in security software.  AI algorithms can detect outliers and any unusual activity that deviates from the normal patters. Currently, it is most commonly used in pattern recognition where it can identify malware or phishing emails-based content and sender.

Artificial Intelligence (AI) algorithms can detect outliers and any unusual activity that deviates from the normal pattern.

Security experts predict that soon companies will incorporate machine learning into all cybersecurity products. This is because machine learning can automate the response side. This could speed up the response to security breaches as soon as malware is detected and help deter email-delivered ransomware or botnets that break down access to websites.

The previous versions of antivirus software could only spot signatures of known malicious software. Now, more advanced machine learning tools can learn to identify collective malware traits rather than only signatures. This allows them to red-flag new types of malware that may not have been detected by earlier antivirus software versions.

Most machine learning cybersecurity solutions use a supervised machine learning approach that provides many advantages over traditional rules-based systems. It does not require a person to manually create, test and deploy. Instead, these models use ” labels ” or historical cases to train themselves.

Cybersecurity for all sizes and budgets

Cybersecurity systems usually generate large amounts of data and threat alerts. Security teams typically don’t have the bandwidth to examine every detail or do it fast enough resulting in gaps or security lapses.  AI can help security teams monitor their systems, detect and analyze threats and trigger a response rapidly as required.

Cybersecurity should remain a top priority for organizations regardless of their size. Even smaller businesses that lack large IT budgets but still have a digital presence, should consider investing in cybersecurity.

At Tricon Infotech, our technology services in machine learning and security can help your business build its cyber defense. Connect with us to learn more about how you can safeguard your business